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A Bayesian Analysis of Income Distribution Image

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  • Atsushi Ishida

Abstract

The purpose of this study is to investigate people’s image of income distribution and its difference by social position from data collected during a 2015 Japanese survey (SSP 2015) by applying Bayesian statistical analytical models. The income distribution image denotes the perceived and estimated income distribution of the individual and is supposed to be a basis of subjective belief on the features of society, including societal average income. In this study, the latent income distribution images were estimated from the observed variable of average income image. Furthermore, differences in income distribution image by social position were analyzed using Bayesian hierarchical models. The differences in income distribution image by age cohort and household income class were examined in terms of the mean (expected value) and the Gini inequality coefficient of the distribution image. It was found that although the distribution image tends to underestimate the average income level and overestimate inequality, the income distribution image could be an incomplete reflection of the income distribution characteristics of the reference group.

Suggested Citation

  • Atsushi Ishida, 2018. "A Bayesian Analysis of Income Distribution Image," SAGE Open, , vol. 8(2), pages 21582440187, May.
    • Handle: RePEc:sae:sagope:v:8:y:2018:i:2:p:2158244018774106
    DOI: 10.1177/2158244018774106
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    References listed on IDEAS

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